Spinal cord injury (SCI) is characterized by marked bone loss at regions below the neurological lesion. The clinical consequence of this reduction in bone is an increased lifetime risk for lower-extremity fracture due to minor trauma that is two times greater than the general population. Fracture risk assessment tools for the general public are inadequate for people living with SCI; the locations of routine fracture do not correspond between these two groups and bone density thresholds defining elevated fracture risk are typical of individuals with SCI. The ability to accurately quantify fracture strength in people with SCI could serve as an important clinical tool to assess fracture risk and objectively identify individuals that could safely participate in active treatment. The objectives of this application are to: Aim 1) develop a numerical method based on quantitative computed tomography (CT) capable of predicting fracture strength at the proximal tibia (a location commonly fractured following SCI), and Aim 2) quantify the change in fracture strength that occurs as a function of time elapsed since SCI. Aim 1 will be accomplished using a combined numerical-experimental study. Cadaveric proximal tibiae will be mechanically loaded until failure. Specimen-specific finite element models will be derived from CT data, and their ability to predict fracture strength determined from a regression analysis of numerical and experimental fracture loads. The predictive value of the finite element models will be compared to statistical models based on CT derived measures of bone mass, density, and structure. Aim 2 will be accomplished using a cross-sectional study design in which the fracture strength of individuals with motor complete SCI, as well as able-bodied controls, will be estimated from CT data. Reductions in fracture strength and bone parameters as a function of time since SCI will be quantified. The long-term goal of this research is to increase the quality of life for people living with SCI by minimizing the incidence of bone fracture in this population. This study will bring biomechanical relevance to the observed bone adaptive changes following SCI and help delineate the most critical determinants of bone fracture strength in this population. This will provide important information that can be used to help guide pharmacologic and exercise interventions that target adaptive changes in parameters most relevant to whole-bone fracture strength. In addition, because the SCI population serves as a model system for disuse osteoporosis, this work will increase our understanding of skeletal fracture in other populations having chronic bone loss and help guide the development of bone strengthening interventions for these individuals.